Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/okisdev/claude-code-fusion/confignpx skills add okisdev/claude-code-fusion --skill configgit clone --depth 1 https://github.com/okisdev/claude-code-fusionWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00050 | $0.01720 |
| Opus 5 | $0.00025 | $0.00860 |
| Sonnet 5 | $0.00010 | $0.00344 |
| Haiku 4.5 | $0.00005 | $0.00172 |
Grade B, and why
config scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
- Read `~/.claude/settings.json` if it exists and report only the `model` key for the main session model. How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Inspect the local model configuration across all peer engines, show what is currently available, and offer targeted edits to the defaults and the per user capability scores. Treat this as the write path counterpart to /fusion:doctor.
Steps:
- Gather current state.
- Capture environment overrides at invocation:
- CLAUDE_CODE_SUBAGENT_MODEL: !
sh -c 'printenv CLAUDE_CODE_SUBAGENT_MODEL || echo "(unset)"' - ANTHROPIC_MODEL: !
sh -c 'printenv ANTHROPIC_MODEL || echo "(unset)"' - ANTHROPIC_DEFAULT_HAIKU_MODEL: !
sh -c 'printenv ANTHROPIC_DEFAULT_HAIKU_MODEL || echo "(unset)"' - ANTHROPIC_DEFAULT_FABLE_MODEL: !
sh -c 'printenv ANTHROPIC_DEFAULT_FABLE_MODEL || echo "(unset)"'
- CLAUDE_CODE_SUBAGENT_MODEL: !
- Read
~/.claude/settings.jsonif it exists and report only themodelkey for the main session model. - Read only the frontmatter of every file in
${CLAUDE_PLUGIN_ROOT}/agents/and report each Claude worker pin'smodelandeffortvalues. - Run
grok modelsto enumerate the account's live model lineup and current default, then extract only model related keys from~/.grok/config.toml. - Extract only the
modelandmodel_reasoning_effortkeys from~/.codex/config.toml. - Run
node "${CLAUDE_PLUGIN_ROOT}/scripts/fusion-config.mjs" showto display the per user quantified engine capability table and its backing file path. Usenode "${CLAUDE_PLUGIN_ROOT}/scripts/fusion-config.mjs" show --jsononly when structured output makes the next edit decision clearer. - Never read or print the full peer config files; extract only model related keys, because those files sit next to credentials and private project settings.
- Do not use
Readon~/.grok/config.tomlor~/.codex/config.toml; use a scopedrgquery that matches only model related keys. - Degrade gracefully per engine. A missing CLI or config file makes that engine's row show as unavailable; it never aborts the command.
- Capture environment overrides at invocation:
- Render one table with columns for configuration surface, current value, available values, and file that owns it. Prefer live enumeration values where available. Include rows for environment overrides, the main session model, Claude worker pins, Grok, and Codex. For unavailable values, write
unavailableand include the reason in the current value or available values cell. Then show the capability table output fromfusion-config.mjs showas its own compact section. - Propose a scorecard when the user asked for a proposal (for example invoked this skill with "propose") or when the capability table from step 2 has no scored models.
- Build one proposed row per engine from the live state gathered in step 1: the grok CLI's current default from
grok models, the codex default from~/.codex/config.tomlchecked against the live codex catalog fromcodex debug models --bundledor a scoped extraction of~/.codex/models_cache.json, and the three Claude worker pins. Model ids come only from that live enumeration, never from memory or a hardcoded list. Skip any engine that came back unavailable. - Draft intelligence, taste, and cost scores from 1 to 5 for each row plus a one line rationale for the notes field, following the table's priority semantics: intelligence proxies correctness and safety, taste is user facing quality, and cost applies only as the final tie breaker. When a row's default model is newer than your knowledge or its standing is uncertain, verify it against live web sources with
WebSearchorWebFetchbefore proposing a score instead of guessing. - Present the whole proposed scorecard in one message, then confirm it with a single
AskUserQuestionround offering accept all, adjust rows, or skip. Never write a score the user has not confirmed; the proposal automates the chore, not the decision. - Apply only the confirmed rows with the existing rescore command from step 4, one invocation per model with
--laneand--notes, then runshowand display the resulting table. Scores choose models and fit inside an existing lane; they do not turn Grok into the ordinary implementation default or otherwise change lane ownership. Ownership changes require an explicit routing policy edit.
- Build one proposed row per engine from the live state gathered in step 1: the grok CLI's current default from
- Offer changes with the
AskUserQuestiontool, then apply only what the user picked.- For Grok, choices must come from the
grok modelsoutput, never from a hardcoded list. Edit~/.grok/config.tomlonly when the user chooses a Grok default change, touch only model related keys, and preserve the rest of the file byte for byte. - For Codex, edit
~/.codex/config.tomlonly when the user chooses a Codex default or reasoning effort change, touch only themodelandmodel_reasoning_effortkeys, and preserve the rest of the file byte for byte. Effort values are per model rather than one fixed list, so read the current model's supported efforts from the live catalog (codex debug models --bundledor a scoped extraction of~/.codex/models_cache.json) before writing one. The config file holds defaults, and explicit per call--modeland--effortoverrides on the first party Codex companion take precedence for one job. - For Claude worker pins, show a caution before asking: this edits the marketplace checkout and will be overwritten by plugin updates. Edit only the plugin agent frontmatter fields the user selected.
- For capability scores and posture, use
node "${CLAUDE_PLUGIN_ROOT}/scripts/fusion-config.mjs" rescore <id> --intelligence N --taste N --cost N [--lane L] [--notes S],node "${CLAUDE_PLUGIN_ROOT}/scripts/fusion-config.mjs" set-cost-profile <text>,node "${CLAUDE_PLUGIN_ROOT}/scripts/fusion-config.mjs" set-posture <judgment|strict>, andnode "${CLAUDE_PLUGIN_ROOT}/scripts/fusion-config.mjs" reset-defaults --yes. This is the same rescore command the proposal step in step 3 batches through.judgmentis the default posture and lets the orchestrator choose execution width and locus per package while guards enforce only collected, verified work; main loop writes are counted and advised there, never blocked.strictrestores the mandatory floors: main loop writes past the budget are denied again, only a dispatch reopens the write window, and the fleet reminder fires on every prompt.reset-defaults --yesresets model routing only and leaves the posture file intact. Suggest scoring again when /fusion:doctor reports model lineup changes or when the user says the available lineup changed. Model routing mutations refresh the live routing rules, butset-posturedoes not, so do not hand edit the generated rules block. - For the main session model, never write
~/.claude/settings.json; advise the user to use/modelinstead. - If an engine is unavailable or lacks live choices, offer no write option for that engine.
- For Grok, choices must come from the
- Close with what changed, what was skipped, and any engines that were unavailable. Advise the user to run
/fusion:doctorto re-audit. Note that new grok sessions pick up config changes, while already running jobs do not.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 40 lines · 50 tokens per session scan B bb465d0f5dc1
config is a skill published in the GitHub repository okisdev/claude-code-fusion (3 stars, last pushed 15d ago), licensed MIT. It adds 50 tokens to every session and 1,720 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
agent-orchestrator
Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.
crewai-multi-agent
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies…
project-orchestration
Orchestrate multi-agent workflows for feature development using planning agents, context handoff, and stage management.
hyperflow
Use when applying Hyperflow's orchestration doctrine in Codex, Antigravity, Grok, or another single-agent surface. Auto-invoke for non-trivial engineering work: build, implement, add, refactor, debug, fix, review, audit, plan, scope, design, brainstorm, ship, or deploy. Trigger with /hyperflow:hyperflow, "use…
skill-creator
Generates Anthropic Skills with complete workflow including GitHub PR creation and local download verification.
Ability Generator
This skill generates markdown skill templates to be later used.